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非接触式共振超声光谱中的光谱内容效应研究

Spectral Content Effects Study in Non-Contact Resonance Ultrasound Spectroscopy.

作者信息

Tayyib Muhammad, Svilainis Linas

机构信息

Department of Electronics Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania.

出版信息

Sensors (Basel). 2025 Jan 5;25(1):265. doi: 10.3390/s25010265.

DOI:10.3390/s25010265
PMID:39797055
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11723329/
Abstract

The application of spread-spectrum signals (arbitrary pulse width and position (APWP) sequences) in air-coupled resonant ultrasound spectroscopy is studied. It was hypothesized that spread-spectrum signal optimization should be based on te signal to noise ratio (SNR). Six APWP signal optimization criteria were proposed for this purpose. Experimental measurements were conducted using a thin polycarbonate sample using two standard spread-spectrum signals, linear and nonlinear frequency modulation, together with six optimized APWP signals. It was found that the performance of APWP signals derived from linear frequency modulation was better. The two best performing optimization criteria are SNR improvement on a linear scale with the SNR as an additional weight and energy improvement on a dB scale. The influence of spectral coverage on measurement errors was evaluated. It was found that it is sufficient to cover the sample resonance peak and the valley. The lowest error rates for density, 3%, and for thickness, 3.5%, were achieved when the upper valley was covered. For velocity, the best result, 5%, was achieved when the lower valley was covered. The lowest error rate for attenuation, 3.8%, was achieved in the case when both valleys were covered. Yet no significant performance degradation was noted when a whole -30 dB passband was covered.

摘要

研究了扩频信号(任意脉冲宽度和位置(APWP)序列)在空气耦合共振超声光谱中的应用。假设扩频信号优化应基于信噪比(SNR)。为此提出了六个APWP信号优化标准。使用薄聚碳酸酯样品,采用两种标准扩频信号(线性和非线性频率调制)以及六个优化的APWP信号进行了实验测量。发现由线性频率调制得到的APWP信号性能更好。表现最佳的两个优化标准是在以SNR为附加权重的线性尺度上提高SNR以及在dB尺度上提高能量。评估了光谱覆盖范围对测量误差的影响。发现覆盖样品共振峰和谷就足够了。当覆盖上谷时,密度的最低误差率为3%,厚度的最低误差率为3.5%。对于速度,当覆盖下谷时获得了最佳结果5%。当两个谷都被覆盖时,衰减的最低误差率为3.8%。然而,当覆盖整个-30 dB通带时,未观察到明显的性能下降。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/e14b15bfaec9/sensors-25-00265-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/b4216cfef0c0/sensors-25-00265-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/a6507dc443b9/sensors-25-00265-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/97c568ca1e0d/sensors-25-00265-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/72cc3ceb4bd0/sensors-25-00265-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/7f7d9656212c/sensors-25-00265-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/62aca8f50dd2/sensors-25-00265-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/19f7849011d1/sensors-25-00265-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/5f42db5a11ee/sensors-25-00265-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/9d6143b2ec2a/sensors-25-00265-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/35279f5902d4/sensors-25-00265-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/d4a2b027e909/sensors-25-00265-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/ca0249472e30/sensors-25-00265-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/8ea143bab53f/sensors-25-00265-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/e14b15bfaec9/sensors-25-00265-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/b4216cfef0c0/sensors-25-00265-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/a6507dc443b9/sensors-25-00265-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/97c568ca1e0d/sensors-25-00265-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/72cc3ceb4bd0/sensors-25-00265-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/7f7d9656212c/sensors-25-00265-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/62aca8f50dd2/sensors-25-00265-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/19f7849011d1/sensors-25-00265-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/5f42db5a11ee/sensors-25-00265-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/9d6143b2ec2a/sensors-25-00265-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/35279f5902d4/sensors-25-00265-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/d4a2b027e909/sensors-25-00265-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/ca0249472e30/sensors-25-00265-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/8ea143bab53f/sensors-25-00265-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bbc/11723329/e14b15bfaec9/sensors-25-00265-g014.jpg

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本文引用的文献

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Rev Sci Instrum. 2019 Dec 1;90(12):121401. doi: 10.1063/1.5123165.
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Instantaneous and non-destructive relative water content estimation from deep learning applied to resonant ultrasonic spectra of plant leaves.基于深度学习的植物叶片共振超声光谱法即时无损相对含水量估计
Plant Methods. 2019 Nov 7;15:128. doi: 10.1186/s13007-019-0511-z. eCollection 2019.
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Ultrasonic Sensing of Plant Water Needs for Agriculture.用于农业的植物水分需求的超声波传感
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Air-coupled ultrasonic resonant spectroscopy for the study of the relationship between plant leaves' elasticity and their water content.用于研究植物叶片弹性与其含水量之间关系的空气耦合超声共振光谱法。
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